A Survey on Secure Computation Based on Homomorphic Encryption in Vehicular Ad Hoc Networks

Sun, Xiaoqiang; Yu, F. Richard; Zhang, Peng; Xie, Weixin; Peng, Xiang

doi:10.3390/s20154253

Cited by 15 publications

(6 citation statements)

References 171 publications

(219 reference statements)

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“…HE allows for certain types of operations on ciphertexts without accessing the secret key. In addition, HE produces an encrypted result in which the decryption matches the computed result on the plaintext [ 25 ]. HE is classified based on a list of mathematical operations on encrypted data.…”

Section: Homomorphic Encryptionmentioning

confidence: 99%

A Review of Homomorphic Encryption for Privacy-Preserving Biometrics

Yang

Wang

Cui

et al. 2023

Sensors

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The advancement of biometric technology has facilitated wide applications of biometrics in law enforcement, border control, healthcare and financial identification and verification. Given the peculiarity of biometric features (e.g., unchangeability, permanence and uniqueness), the security of biometric data is a key area of research. Security and privacy are vital to enacting integrity, reliability and availability in biometric-related applications. Homomorphic encryption (HE) is concerned with data manipulation in the cryptographic domain, thus addressing the security and privacy issues faced by biometrics. This survey provides a comprehensive review of state-of-the-art HE research in the context of biometrics. Detailed analyses and discussions are conducted on various HE approaches to biometric security according to the categories of different biometric traits. Moreover, this review presents the perspective of integrating HE with other emerging technologies (e.g., machine/deep learning and blockchain) for biometric security. Finally, based on the latest development of HE in biometrics, challenges and future research directions are put forward.

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Section: Homomorphic Encryptionmentioning

confidence: 99%

A Review of Homomorphic Encryption for Privacy-Preserving Biometrics

Yang

Wang

Cui

et al. 2023

Sensors

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“…Later, on computing EN C(u × v + v) we obtain same result as the homomorphic encryption EN C(u) × EN C(v) + EN C(v). Moreover, any search operation over the encrypted data can be performed and thereby enhances multi-party computation [60]. Homomorphic encryption was proposed by Rivest et al in 1978 [61].…”

Section: Homomorphic Encryption Based Schemesmentioning

confidence: 99%

Privacy-preserving Authentication Protocols in VANET: A Review

Nath

Choudhury

2023

Preprint

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Vehicular Ad hoc Network (VANET) is a versatile and ad hoc network, where the vehicles must be authenticated before sharing any critical information. During authentication, privacy of the users must be preserved. There are several surveys on privacy-preserving authentication schemes in VANET. However, none of them are focused on the ability of the schemes to address different security issues and their robustness against security attacks. In this paper, we present a review on various privacy-preserving authentication schemes in VANET. These schemes may be categorized into several types like symmetric/asymmetric key cryptography based schemes, digital signature based schemes, ID cryptography based schemes, pseudonym based schemes, homomorphic encryption based schemes and blockchain based schemes. A comprehensive study of the prominent schemes, with regards to their effectiveness in addressing different security issues and their robustness against possible attacks, has been performed. Open issues and scope for future work are also highlighted.

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“…Homomorphic encryption is based on the principle of processing data without the requirement of decrypting it [15][16][17]. Data confidentiality is one of the primary principles of implementing the encryption system in untrusted server systems.…”

Section: Existing Researchmentioning

confidence: 99%

Homomorphic Encryption Based Privacy-Preservation for IoMT

et al. 2021

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Healthcare applications store private user data on cloud servers and perform computation operations that support several patient diagnoses. Growing cyber-attacks on hospital systems result in user data being held at ransom. Furthermore, mathematical operations on data stored in the Cloud are exposed to untrusted external entities that sell private data for financial gain. In this paper, we propose a privacy-preserving scheme using homomorphic encryption to secure medical plaintext data from being accessed by attackers. Secret sharing distributes computations to several virtual nodes on the edge and masks all arithmetic operations, preventing untrusted cloud servers from learning the tasks performed on the encrypted patient data. Virtual edge nodes benefit from cloud computing resources to accomplish computing-intensive mathematical functions and reduce latency in device–edge node data transmission. A comparative analysis with existing studies demonstrates that homomorphically encrypted data stored at the edge preserves data privacy and integrity. Furthermore, secret sharing-based multi-node computation using virtual nodes ensures data confidentiality from untrusted cloud networks.

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A Survey on Secure Computation Based on Homomorphic Encryption in Vehicular Ad Hoc Networks

Cited by 15 publications

References 171 publications

A Review of Homomorphic Encryption for Privacy-Preserving Biometrics

A Review of Homomorphic Encryption for Privacy-Preserving Biometrics

Privacy-preserving Authentication Protocols in VANET: A Review

Homomorphic Encryption Based Privacy-Preservation for IoMT

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